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add candle difference calculation to dataprovider

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This commit is contained in:
Timothy Pogue 2022-11-28 11:02:03 -07:00
parent 89338fa677
commit c050eb8b8b
1 changed files with 23 additions and 17 deletions
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40
freqtrade/data/dataprovider.py
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@ -9,7 +9,7 @@ from collections import deque
from datetime import datetime, timezone
from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame, concat
from pandas import DataFrame, concat, to_timedelta
from freqtrade.configuration import TimeRange
from freqtrade.constants import Config, ListPairsWithTimeframes, PairWithTimeframe
@ -176,24 +176,30 @@ class DataProvider:
"""
pair_key = (pair, timeframe, candle_type)
if producer_name not in self.__producer_pairs_df:
if (producer_name not in self.__producer_pairs_df) \
or (pair_key not in self.__producer_pairs_df[producer_name]):
# We don't have data from this producer yet,
# so we can't append a candle
return (False, 999)
if pair_key not in self.__producer_pairs_df[producer_name]:
# We don't have data for this pair_key,
# so we can't append a candle
return (False, 999)
# CHECK FOR MISSING CANDLES
# Calculate difference between last candle in local dataframe
# and first candle in incoming dataframe. Take difference and divide
# by timeframe to find out how many candles we still need. If 1
# then the incoming candle is the right candle. If more than 1,
# return (False, missing candles - 1)
# sor we don't have data for this pair_key
# return False and 1000 for the full df
return (False, 1000)
existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
# CHECK FOR MISSING CANDLES
timeframe_delta = to_timedelta(timeframe) # Convert the timeframe to a timedelta for pandas
local_last = existing_df.iloc[-1]['date'] # We want the last date from our copy of data
incoming_first = dataframe.iloc[0]['date'] # We want the first date from the incoming data
candle_difference = (incoming_first - local_last) / timeframe_delta
# If the difference divided by the timeframe is 1, then this
# is the candle we want and the incoming data isn't missing any.
# If the candle_difference is more than 1, that means
# we missed some candles between our data and the incoming
# so return False and candle_difference.
if candle_difference > 1:
return (False, candle_difference)
appended_df = self._append_candle_to_dataframe(existing_df, dataframe)
# Everything is good, we appended
@ -212,7 +218,7 @@ class DataProvider:
existing = concat([existing, new])
# Only keep the last 1500 candles in memory
existing = existing[-1500:] if len(existing) > 1000 else existing
existing = existing[-1500:] if len(existing) > 1500 else existing
return existing